********************************************************************************
*Table A3;  Column 1 
********************************************************************************
clear all
set matsize 10000
set maxvar 40000
set more off
global data " "
global dir " "
use $data/estimation_sample_blacks, clear

drop if bw==.|gest_det==.


****************************************
preserve
gen Post0=0
replace Post0=1 if index==0

gen Post1=0
replace Post1=1 if index==1

gen Post2=0
replace Post2=1 if index==2

gen Post3=0
replace Post3=1 if index==3

gen Post4=0
replace Post4=1 if index>=4


global treat_var "Post0 Post1 Post2 Post3 Post4"
global state_var "Exitexam Perstudentexpenditure Studentteacherratio Povertyrate Unemploymentrate"
foreach x in $treat_var{
sum `x', meanonly
scalar mean`x'=r(mean)
}

reg mothers_age $treat_var $state_var  i.tbo i.male  i.division#c.by i.by i.mom_birth_state, cluster(mom_birth_state)

local Z=meanPost0+meanPost1+meanPost2+meanPost3+meanPost4
lincom (_b[Post0]*meanPost0/`Z')+(_b[Post1]*meanPost1/`Z')+(_b[Post2]*meanPost2/`Z')+(_b[Post3]*meanPost3/`Z')+(_b[Post4]*meanPost4/`Z')
restore
********************************************************************************

set seed 23260513
capture postclose placebo		  
postfile placebo b using "$data/table_a3_c1", replace
forvalues i=1/500 {
use $data/estimation_sample_blacks, clear

drop if bw==.|gest_det==.

****************************************
preserve
bsample, cluster(mom_birth_state)

gen Post0=0
replace Post0=1 if index==0

gen Post1=0
replace Post1=1 if index==1

gen Post2=0
replace Post2=1 if index==2

gen Post3=0
replace Post3=1 if index==3

gen Post4=0
replace Post4=1 if index>=4


global treat_var "Post0 Post1 Post2 Post3 Post4"
global state_var "Exitexam Perstudentexpenditure Studentteacherratio Povertyrate Unemploymentrate"
foreach x in $treat_var{
sum `x', meanonly
scalar mean`x'=r(mean)
}
qui reg mothers_age $treat_var $state_var   i.tbo i.male  i.division#c.by i.by i.mom_birth_state 
local V=meanPost0+meanPost1+meanPost2+meanPost3+meanPost4
local c_weighted=(_b[Post0]*meanPost0/`V')+(_b[Post1]*meanPost1/`V')+(_b[Post2]*meanPost2/`V')+(_b[Post3]*meanPost3/`V')+(_b[Post4]*meanPost4/`V')
post placebo (`c_weighted')
restore
}

postclose placebo



use table_a3_c1, clear

sum  /****Std Dev is the standard error of the weighted point estimate.*/


********************************************************************************
*Table A3;  Column 2 
********************************************************************************
clear all
set matsize 10000
set maxvar 40000
set more off
global data " "
global dir " "
use $data/estimation_sample_blacks, clear

drop if bw==.|gest_det==.

gen age20=0
replace age20=1 if mothers_age<=20

****************************************
preserve
gen Post0=0
replace Post0=1 if index==0

gen Post1=0
replace Post1=1 if index==1

gen Post2=0
replace Post2=1 if index==2

gen Post3=0
replace Post3=1 if index==3

gen Post4=0
replace Post4=1 if index>=4


global treat_var "Post0 Post1 Post2 Post3 Post4"
global state_var "Exitexam Perstudentexpenditure Studentteacherratio Povertyrate Unemploymentrate"
foreach x in $treat_var{
sum `x', meanonly
scalar mean`x'=r(mean)
}

reg age20 $treat_var $state_var  i.tbo i.male  i.division#c.by i.by i.mom_birth_state, cluster(mom_birth_state)

local Z=meanPost0+meanPost1+meanPost2+meanPost3+meanPost4
lincom (_b[Post0]*meanPost0/`Z')+(_b[Post1]*meanPost1/`Z')+(_b[Post2]*meanPost2/`Z')+(_b[Post3]*meanPost3/`Z')+(_b[Post4]*meanPost4/`Z')
restore
********************************************************************************

set seed 23260513
capture postclose placebo		  
postfile placebo b using "$data/table_a3_c2", replace
forvalues i=1/500 {
use $data/estimation_sample_blacks, clear

drop if bw==.|gest_det==.
gen age20=0
replace age20=1 if mothers_age<=20

preserve
bsample, cluster(mom_birth_state)

gen Post0=0
replace Post0=1 if index==0

gen Post1=0
replace Post1=1 if index==1

gen Post2=0
replace Post2=1 if index==2

gen Post3=0
replace Post3=1 if index==3

gen Post4=0
replace Post4=1 if index>=4


global treat_var "Post0 Post1 Post2 Post3 Post4"
global state_var "Exitexam Perstudentexpenditure Studentteacherratio Povertyrate Unemploymentrate"
foreach x in $treat_var{
sum `x', meanonly
scalar mean`x'=r(mean)
}
qui reg age20 $treat_var $state_var   i.tbo i.male  i.division#c.by i.by i.mom_birth_state 
local V=meanPost0+meanPost1+meanPost2+meanPost3+meanPost4
local c_weighted=(_b[Post0]*meanPost0/`V')+(_b[Post1]*meanPost1/`V')+(_b[Post2]*meanPost2/`V')+(_b[Post3]*meanPost3/`V')+(_b[Post4]*meanPost4/`V')
post placebo (`c_weighted')
restore
}

postclose placebo



use table_a3_c2, clear

sum  /****Std Dev is the standard error of the weighted point estimate.*/


********************************************************************************
*Table A3;  Column 3 
********************************************************************************
clear all
set matsize 10000
set maxvar 40000
set more off
global data " "
global dir " "
use $data/estimation_sample_blacks, clear

drop if bw==.|gest_det==.


egen p1=pctile(mothers_age), p(50)
gen median_below=0
replace median_below=1 if mothers_age<p1
****************************************
preserve
gen Post0=0
replace Post0=1 if index==0

gen Post1=0
replace Post1=1 if index==1

gen Post2=0
replace Post2=1 if index==2

gen Post3=0
replace Post3=1 if index==3

gen Post4=0
replace Post4=1 if index>=4


global treat_var "Post0 Post1 Post2 Post3 Post4"
global state_var "Exitexam Perstudentexpenditure Studentteacherratio Povertyrate Unemploymentrate"
foreach x in $treat_var{
sum `x', meanonly
scalar mean`x'=r(mean)
}

reg median_below $treat_var $state_var  i.tbo i.male  i.division#c.by i.by i.mom_birth_state, cluster(mom_birth_state)

local Z=meanPost0+meanPost1+meanPost2+meanPost3+meanPost4
lincom (_b[Post0]*meanPost0/`Z')+(_b[Post1]*meanPost1/`Z')+(_b[Post2]*meanPost2/`Z')+(_b[Post3]*meanPost3/`Z')+(_b[Post4]*meanPost4/`Z')
restore
********************************************************************************

set seed 23260513
capture postclose placebo		  
postfile placebo b using "$data/table_a3_c3", replace
forvalues i=1/500 {
use $data/estimation_sample_blacks, clear

drop if bw==.|gest_det==.

egen p1=pctile(mothers_age), p(50)
gen median_below=0
replace median_below=1 if mothers_age<p1

preserve
bsample, cluster(mom_birth_state)

gen Post0=0
replace Post0=1 if index==0

gen Post1=0
replace Post1=1 if index==1

gen Post2=0
replace Post2=1 if index==2

gen Post3=0
replace Post3=1 if index==3

gen Post4=0
replace Post4=1 if index>=4


global treat_var "Post0 Post1 Post2 Post3 Post4"
global state_var "Exitexam Perstudentexpenditure Studentteacherratio Povertyrate Unemploymentrate"
foreach x in $treat_var{
sum `x', meanonly
scalar mean`x'=r(mean)
}
qui reg median_below $treat_var $state_var   i.tbo i.male  i.division#c.by i.by i.mom_birth_state 
local V=meanPost0+meanPost1+meanPost2+meanPost3+meanPost4
local c_weighted=(_b[Post0]*meanPost0/`V')+(_b[Post1]*meanPost1/`V')+(_b[Post2]*meanPost2/`V')+(_b[Post3]*meanPost3/`V')+(_b[Post4]*meanPost4/`V')
post placebo (`c_weighted')
restore
}

postclose placebo



use table_a3_c3, clear

sum  /****Std Dev is the standard error of the weighted point estimate.*/



********************************************************************************
*Table A3;  Column 4 
********************************************************************************
clear all
set matsize 10000
set maxvar 40000
set more off
global data " "
global dir " "
use $data/estimation_sample_blacks, clear

drop if bw==.|gest_det==.


preserve
gen Post0=0
replace Post0=1 if index==0

gen Post1=0
replace Post1=1 if index==1

gen Post2=0
replace Post2=1 if index==2

gen Post3=0
replace Post3=1 if index==3

gen Post4=0
replace Post4=1 if index>=4


global treat_var "Post0 Post1 Post2 Post3 Post4"
global state_var "Exitexam Perstudentexpenditure Studentteacherratio Povertyrate Unemploymentrate"
foreach x in $treat_var{
sum `x', meanonly
scalar mean`x'=r(mean)
}

reg married $treat_var $state_var  i.age_cat i.birth_month i.year  i.tbo i.male  i.division#c.by i.by i.mom_birth_state, cluster(mom_birth_state)

local Z=meanPost0+meanPost1+meanPost2+meanPost3+meanPost4
lincom (_b[Post0]*meanPost0/`Z')+(_b[Post1]*meanPost1/`Z')+(_b[Post2]*meanPost2/`Z')+(_b[Post3]*meanPost3/`Z')+(_b[Post4]*meanPost4/`Z')
restore
********************************************************************************

set seed 23260513
capture postclose placebo		  
postfile placebo b using "$data/table_a3_c4", replace
forvalues i=1/500 {
use $data/estimation_sample_blacks, clear


drop if bw==.|gest_det==.


preserve
bsample, cluster(mom_birth_state)

gen Post0=0
replace Post0=1 if index==0

gen Post1=0
replace Post1=1 if index==1

gen Post2=0
replace Post2=1 if index==2

gen Post3=0
replace Post3=1 if index==3

gen Post4=0
replace Post4=1 if index>=4


global treat_var "Post0 Post1 Post2 Post3 Post4"
global state_var "Exitexam Perstudentexpenditure Studentteacherratio Povertyrate Unemploymentrate"
foreach x in $treat_var{
sum `x', meanonly
scalar mean`x'=r(mean)
}
qui reg married $treat_var $state_var  i.age_cat i.birth_month i.year  i.tbo i.male  i.division#c.by i.by i.mom_birth_state 
local V=meanPost0+meanPost1+meanPost2+meanPost3+meanPost4
local c_weighted=(_b[Post0]*meanPost0/`V')+(_b[Post1]*meanPost1/`V')+(_b[Post2]*meanPost2/`V')+(_b[Post3]*meanPost3/`V')+(_b[Post4]*meanPost4/`V')
post placebo (`c_weighted')
restore
}

postclose placebo



use table_a3_c4, clear

sum   /****Std Dev is the standard error of the weighted point estimate.*/




********************************************************************************
*Table A3;  Column 5 
********************************************************************************
clear all
set matsize 10000
set maxvar 40000
set more off
global data " "
global dir " "
use $data/estimation_sample_blacks, clear

drop if bw==.|gest_det==.



preserve
gen Post0=0
replace Post0=1 if index==0

gen Post1=0
replace Post1=1 if index==1

gen Post2=0
replace Post2=1 if index==2

gen Post3=0
replace Post3=1 if index==3

gen Post4=0
replace Post4=1 if index>=4


global treat_var "Post0 Post1 Post2 Post3 Post4"
global state_var "Exitexam Perstudentexpenditure Studentteacherratio Povertyrate Unemploymentrate"
foreach x in $treat_var{
sum `x', meanonly
scalar mean`x'=r(mean)
}

reg male $treat_var $state_var  i.age_cat i.birth_month i.year  i.tbo i.married  i.division#c.by i.by i.mom_birth_state, cluster(mom_birth_state)

local Z=meanPost0+meanPost1+meanPost2+meanPost3+meanPost4
lincom (_b[Post0]*meanPost0/`Z')+(_b[Post1]*meanPost1/`Z')+(_b[Post2]*meanPost2/`Z')+(_b[Post3]*meanPost3/`Z')+(_b[Post4]*meanPost4/`Z')
restore
********************************************************************************

set seed 23260513
capture postclose placebo		  
postfile placebo b using "$data/table_a3_c5", replace
forvalues i=1/500 {
use $data/estimation_sample_blacks, clear



drop if bw==.|gest_det==.


preserve
bsample, cluster(mom_birth_state)

gen Post0=0
replace Post0=1 if index==0

gen Post1=0
replace Post1=1 if index==1

gen Post2=0
replace Post2=1 if index==2

gen Post3=0
replace Post3=1 if index==3

gen Post4=0
replace Post4=1 if index>=4


global treat_var "Post0 Post1 Post2 Post3 Post4"
global state_var "Exitexam Perstudentexpenditure Studentteacherratio Povertyrate Unemploymentrate"
foreach x in $treat_var{
sum `x', meanonly
scalar mean`x'=r(mean)
}
qui reg male $treat_var $state_var  i.age_cat i.birth_month i.year  i.tbo i.married  i.division#c.by i.by i.mom_birth_state 
local V=meanPost0+meanPost1+meanPost2+meanPost3+meanPost4
local c_weighted=(_b[Post0]*meanPost0/`V')+(_b[Post1]*meanPost1/`V')+(_b[Post2]*meanPost2/`V')+(_b[Post3]*meanPost3/`V')+(_b[Post4]*meanPost4/`V')
post placebo (`c_weighted')
restore
}

postclose placebo

use table_a3_c5, clear

sum /****Std Dev is the standard error of the weighted point estimate.*/




********************************************************************************
*Table A3;  Column 6 
********************************************************************************
clear all
set matsize 10000
set maxvar 40000
set more off
global data " "
global dir " "
use $data/estimation_sample_whites, clear

drop if bw==.|gest_det==.


preserve
gen Post0=0
replace Post0=1 if index==0

gen Post1=0
replace Post1=1 if index==1

gen Post2=0
replace Post2=1 if index==2

gen Post3=0
replace Post3=1 if index==3

gen Post4=0
replace Post4=1 if index>=4


global treat_var "Post0 Post1 Post2 Post3 Post4"
global state_var "Exitexam Perstudentexpenditure Studentteacherratio Povertyrate Unemploymentrate"
foreach x in $treat_var{
sum `x', meanonly
scalar mean`x'=r(mean)
}

reg mothers_age $treat_var $state_var  i.tbo i.male  i.division#c.by i.by i.mom_birth_state, cluster(mom_birth_state)

local Z=meanPost0+meanPost1+meanPost2+meanPost3+meanPost4
lincom (_b[Post0]*meanPost0/`Z')+(_b[Post1]*meanPost1/`Z')+(_b[Post2]*meanPost2/`Z')+(_b[Post3]*meanPost3/`Z')+(_b[Post4]*meanPost4/`Z')
restore
********************************************************************************

set seed 23260513
capture postclose placebo		  
postfile placebo b using "$data/table_a3_c6", replace
forvalues i=1/500 {
use $data/estimation_sample_whites, clear

drop if bw==.|gest_det==.

preserve
bsample, cluster(mom_birth_state)

gen Post0=0
replace Post0=1 if index==0

gen Post1=0
replace Post1=1 if index==1

gen Post2=0
replace Post2=1 if index==2

gen Post3=0
replace Post3=1 if index==3

gen Post4=0
replace Post4=1 if index>=4


global treat_var "Post0 Post1 Post2 Post3 Post4"
global state_var "Exitexam Perstudentexpenditure Studentteacherratio Povertyrate Unemploymentrate"
foreach x in $treat_var{
sum `x', meanonly
scalar mean`x'=r(mean)
}
qui reg mothers_age $treat_var $state_var   i.tbo i.male  i.division#c.by i.by i.mom_birth_state 
local V=meanPost0+meanPost1+meanPost2+meanPost3+meanPost4
local c_weighted=(_b[Post0]*meanPost0/`V')+(_b[Post1]*meanPost1/`V')+(_b[Post2]*meanPost2/`V')+(_b[Post3]*meanPost3/`V')+(_b[Post4]*meanPost4/`V')
post placebo (`c_weighted')
restore
}

postclose placebo



use table_a3_c6, clear

sum  /****Std Dev is the standard error of the weighted point estimate.*/


********************************************************************************
*Table A3;  Column 7 
********************************************************************************
clear all
set matsize 10000
set maxvar 40000
set more off
global data " "
global dir " "
use $data/estimation_sample_whites, clear

drop if bw==.|gest_det==.

gen age20=0
replace age20=1 if mothers_age<=20

preserve
gen Post0=0
replace Post0=1 if index==0

gen Post1=0
replace Post1=1 if index==1

gen Post2=0
replace Post2=1 if index==2

gen Post3=0
replace Post3=1 if index==3

gen Post4=0
replace Post4=1 if index>=4


global treat_var "Post0 Post1 Post2 Post3 Post4"
global state_var "Exitexam Perstudentexpenditure Studentteacherratio Povertyrate Unemploymentrate"
foreach x in $treat_var{
sum `x', meanonly
scalar mean`x'=r(mean)
}

reg age20 $treat_var $state_var  i.tbo i.male  i.division#c.by i.by i.mom_birth_state, cluster(mom_birth_state)

local Z=meanPost0+meanPost1+meanPost2+meanPost3+meanPost4
lincom (_b[Post0]*meanPost0/`Z')+(_b[Post1]*meanPost1/`Z')+(_b[Post2]*meanPost2/`Z')+(_b[Post3]*meanPost3/`Z')+(_b[Post4]*meanPost4/`Z')
restore
********************************************************************************

set seed 23260513
capture postclose placebo		  
postfile placebo b using "$data/table_a3_c7", replace
forvalues i=1/500 {
use $data/estimation_sample_whites, clear

drop if bw==.|gest_det==.
gen age20=0
replace age20=1 if mothers_age<=20


preserve
bsample, cluster(mom_birth_state)

gen Post0=0
replace Post0=1 if index==0

gen Post1=0
replace Post1=1 if index==1

gen Post2=0
replace Post2=1 if index==2

gen Post3=0
replace Post3=1 if index==3

gen Post4=0
replace Post4=1 if index>=4


global treat_var "Post0 Post1 Post2 Post3 Post4"
global state_var "Exitexam Perstudentexpenditure Studentteacherratio Povertyrate Unemploymentrate"
foreach x in $treat_var{
sum `x', meanonly
scalar mean`x'=r(mean)
}
qui reg age20 $treat_var $state_var   i.tbo i.male  i.division#c.by i.by i.mom_birth_state 
local V=meanPost0+meanPost1+meanPost2+meanPost3+meanPost4
local c_weighted=(_b[Post0]*meanPost0/`V')+(_b[Post1]*meanPost1/`V')+(_b[Post2]*meanPost2/`V')+(_b[Post3]*meanPost3/`V')+(_b[Post4]*meanPost4/`V')
post placebo (`c_weighted')
restore
}

postclose placebo



use table_a3_c7, clear

sum  /****Std Dev is the standard error of the weighted point estimate.*/


********************************************************************************
*Table A3;  Column 8 
********************************************************************************
clear all
set matsize 10000
set maxvar 40000
set more off
global data " "
global dir " "
use $data/estimation_sample_whites, clear

drop if bw==.|gest_det==.


egen p1=pctile(mothers_age), p(50)
gen median_below=0
replace median_below=1 if mothers_age<p1

preserve
gen Post0=0
replace Post0=1 if index==0

gen Post1=0
replace Post1=1 if index==1

gen Post2=0
replace Post2=1 if index==2

gen Post3=0
replace Post3=1 if index==3

gen Post4=0
replace Post4=1 if index>=4


global treat_var "Post0 Post1 Post2 Post3 Post4"
global state_var "Exitexam Perstudentexpenditure Studentteacherratio Povertyrate Unemploymentrate"
foreach x in $treat_var{
sum `x', meanonly
scalar mean`x'=r(mean)
}

reg median_below $treat_var $state_var  i.tbo i.male  i.division#c.by i.by i.mom_birth_state, cluster(mom_birth_state)

local Z=meanPost0+meanPost1+meanPost2+meanPost3+meanPost4
lincom (_b[Post0]*meanPost0/`Z')+(_b[Post1]*meanPost1/`Z')+(_b[Post2]*meanPost2/`Z')+(_b[Post3]*meanPost3/`Z')+(_b[Post4]*meanPost4/`Z')
restore
********************************************************************************

set seed 23260513
capture postclose placebo		  
postfile placebo b using "$data/table_a3_c8", replace
forvalues i=1/500 {
use $data/estimation_sample_whites, clear

drop if bw==.|gest_det==.

egen p1=pctile(mothers_age), p(50)
gen median_below=0
replace median_below=1 if mothers_age<p1

preserve
bsample, cluster(mom_birth_state)

gen Post0=0
replace Post0=1 if index==0

gen Post1=0
replace Post1=1 if index==1

gen Post2=0
replace Post2=1 if index==2

gen Post3=0
replace Post3=1 if index==3

gen Post4=0
replace Post4=1 if index>=4


global treat_var "Post0 Post1 Post2 Post3 Post4"
global state_var "Exitexam Perstudentexpenditure Studentteacherratio Povertyrate Unemploymentrate"
foreach x in $treat_var{
sum `x', meanonly
scalar mean`x'=r(mean)
}
qui reg median_below $treat_var $state_var   i.tbo i.male  i.division#c.by i.by i.mom_birth_state 
local V=meanPost0+meanPost1+meanPost2+meanPost3+meanPost4
local c_weighted=(_b[Post0]*meanPost0/`V')+(_b[Post1]*meanPost1/`V')+(_b[Post2]*meanPost2/`V')+(_b[Post3]*meanPost3/`V')+(_b[Post4]*meanPost4/`V')
post placebo (`c_weighted')
restore
}

postclose placebo



use table_a3_c8, clear

sum  /****Std Dev is the standard error of the weighted point estimate.*/



********************************************************************************
*Table A3;  Column 9 
********************************************************************************
clear all
set matsize 10000
set maxvar 40000
set more off
global data " "
global dir " "
use $data/estimation_sample_whites, clear

drop if bw==.|gest_det==.


preserve
gen Post0=0
replace Post0=1 if index==0

gen Post1=0
replace Post1=1 if index==1

gen Post2=0
replace Post2=1 if index==2

gen Post3=0
replace Post3=1 if index==3

gen Post4=0
replace Post4=1 if index>=4


global treat_var "Post0 Post1 Post2 Post3 Post4"
global state_var "Exitexam Perstudentexpenditure Studentteacherratio Povertyrate Unemploymentrate"
foreach x in $treat_var{
sum `x', meanonly
scalar mean`x'=r(mean)
}

reg married $treat_var $state_var  i.age_cat i.birth_month i.year  i.tbo i.male  i.division#c.by i.by i.mom_birth_state, cluster(mom_birth_state)

local Z=meanPost0+meanPost1+meanPost2+meanPost3+meanPost4
lincom (_b[Post0]*meanPost0/`Z')+(_b[Post1]*meanPost1/`Z')+(_b[Post2]*meanPost2/`Z')+(_b[Post3]*meanPost3/`Z')+(_b[Post4]*meanPost4/`Z')
restore
********************************************************************************

set seed 23260513
capture postclose placebo		  
postfile placebo b using "$data/table_a3_c9", replace
forvalues i=1/500 {
use $data/estimation_sample_whites, clear


drop if bw==.|gest_det==.


preserve
bsample, cluster(mom_birth_state)

gen Post0=0
replace Post0=1 if index==0

gen Post1=0
replace Post1=1 if index==1

gen Post2=0
replace Post2=1 if index==2

gen Post3=0
replace Post3=1 if index==3

gen Post4=0
replace Post4=1 if index>=4


global treat_var "Post0 Post1 Post2 Post3 Post4"
global state_var "Exitexam Perstudentexpenditure Studentteacherratio Povertyrate Unemploymentrate"
foreach x in $treat_var{
sum `x', meanonly
scalar mean`x'=r(mean)
}
qui reg married $treat_var $state_var  i.age_cat i.birth_month i.year  i.tbo i.male  i.division#c.by i.by i.mom_birth_state 
local V=meanPost0+meanPost1+meanPost2+meanPost3+meanPost4
local c_weighted=(_b[Post0]*meanPost0/`V')+(_b[Post1]*meanPost1/`V')+(_b[Post2]*meanPost2/`V')+(_b[Post3]*meanPost3/`V')+(_b[Post4]*meanPost4/`V')
post placebo (`c_weighted')
restore
}

postclose placebo



use table_a3_c9, clear

sum   /****Std Dev is the standard error of the weighted point estimate.*/




********************************************************************************
*Table A3;  Column 10 
********************************************************************************
clear all
set matsize 10000
set maxvar 40000
set more off
global data " "
global dir " "
use $data/estimation_sample_whites, clear

drop if bw==.|gest_det==.



preserve
gen Post0=0
replace Post0=1 if index==0

gen Post1=0
replace Post1=1 if index==1

gen Post2=0
replace Post2=1 if index==2

gen Post3=0
replace Post3=1 if index==3

gen Post4=0
replace Post4=1 if index>=4


global treat_var "Post0 Post1 Post2 Post3 Post4"
global state_var "Exitexam Perstudentexpenditure Studentteacherratio Povertyrate Unemploymentrate"
foreach x in $treat_var{
sum `x', meanonly
scalar mean`x'=r(mean)
}

reg male $treat_var $state_var  i.age_cat i.birth_month i.year  i.tbo i.married  i.division#c.by i.by i.mom_birth_state, cluster(mom_birth_state)

local Z=meanPost0+meanPost1+meanPost2+meanPost3+meanPost4
lincom (_b[Post0]*meanPost0/`Z')+(_b[Post1]*meanPost1/`Z')+(_b[Post2]*meanPost2/`Z')+(_b[Post3]*meanPost3/`Z')+(_b[Post4]*meanPost4/`Z')
restore
********************************************************************************

set seed 23260513
capture postclose placebo		  
postfile placebo b using "$data/table_a3_c10", replace
forvalues i=1/500 {
use $data/estimation_sample_whites, clear



drop if bw==.|gest_det==.


preserve
bsample, cluster(mom_birth_state)

gen Post0=0
replace Post0=1 if index==0

gen Post1=0
replace Post1=1 if index==1

gen Post2=0
replace Post2=1 if index==2

gen Post3=0
replace Post3=1 if index==3

gen Post4=0
replace Post4=1 if index>=4


global treat_var "Post0 Post1 Post2 Post3 Post4"
global state_var "Exitexam Perstudentexpenditure Studentteacherratio Povertyrate Unemploymentrate"
foreach x in $treat_var{
sum `x', meanonly
scalar mean`x'=r(mean)
}
qui reg male $treat_var $state_var  i.age_cat i.birth_month i.year  i.tbo i.married  i.division#c.by i.by i.mom_birth_state 
local V=meanPost0+meanPost1+meanPost2+meanPost3+meanPost4
local c_weighted=(_b[Post0]*meanPost0/`V')+(_b[Post1]*meanPost1/`V')+(_b[Post2]*meanPost2/`V')+(_b[Post3]*meanPost3/`V')+(_b[Post4]*meanPost4/`V')
post placebo (`c_weighted')
restore
}

postclose placebo

use table_a3_c10, clear

sum /****Std Dev is the standard error of the weighted point estimate.*/





